BIG Data Hadoop Developer training chennai- PERIDOT SYSTEMS

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Pre-requisites:

To learn hadoop developer, core java and good analytical skills are needed. We provide a complimentary Course “Java Essentials for Hadoop” to all learners to brush up java skills needed to write Map reduce Programs.

Target learners:

If you are interested in Architecture & Fundamentals, Map reduces Programming and real time Analytics then you can be a Hadoop developer.

Content:

Introduction

Hadoop Motivation

Traditional large-scale system problem
Introducing Hadoop
Hadoopable problems
Basic concepts and HDFS

Hadoop projects and components
Hadoop distributed file systems
Map Reduce

Map reduce overviews
Example:Wordcount
Mappers
Reducers
Hadoop cluster and ecosystems

Hadoop cluster overview
Hadoop job and task
Writing a Map Reduce Program using Java

Basic Map Reduce API Concepts
Writing Map Reduce Drivers, Mappers, and reducers
Speeding Up Hadoop Development by Using Eclipse
Differences Between the Old and New Map reduce API
Writing a Map Reduce Program Using Streaming

Writing Mappers and Reducers using streaming API
Unit Testing Map Reduce Programs

Unit Testing
The JUnit and MRUnit Testing Frameworks
Writing Unit Tests with MRUnit
Running Unit Tests
Unit Testing Map Reduce Programs

Unit Testing
The JUnit and MRUnit Testing Frameworks
Writing Unit Tests with MRUnit
Running Unit Tests
Practical Development Tips and Techniques

Strategies for Debugging Map Reduce Code
Testing Map Reduce Code Locally by Using Local JobRunner
Writing and Viewing Log Files
Retrieving Job Information with Counters
Reusing Objects
Creating Map-Only Map Reduce Jobs
Practical Development Tips and Techniques

Strategies for Debugging Map Reduce Code
Testing Map Reduce Code Locally by Using LocalJobRunner
Writing and Viewing Log Files
Retrieving Job Information with Counters
Reusing Objects
Creating Map-Only Map Reduce Jobs
Practical Development Tips and Techniques

Strategies for Debugging Map Reduce Code
Testing Map Reduce Code Locally by Using LocalJobRunner
Writing and Viewing Log Files
Retrieving Job Information with Counters
Reusing Objects
Creating Map-Only Map Reduce Jobs
Common Map Reduce Algorithms

Sorting and Searching Large Data Sets
Indexing Data
Computing Term Frequency — Inverse Document Frequency
Calculating Word Co-Occurrence
Performing Secondary Sort
Joining Data Sets in Map Reduce Jobs

Writing a Map-Side Join
Writing a Reduce-Side Join
Integrating Hadoop into the Enterprise Workflow

Integrating Hadoop into an Existing Enterprise
Loading Data from an RDBMS into HDFS by Using Sqoop
Managing Real-Time Data Using Flume
Accessing HDFS from Legacy Systems with FuseDFS and HttpFS
An Introduction to Hive, Imapala, and Pig

The Motivation for Hive, Impala, and Pig
Hive Overview
Impala Overview
Pig Overview
Choosing Between Hive, Impala, and Pig
An Introduction to Oozie

Introduction to Oozie
Creating Oozie Workflows
Conclusion

For More Details,

Contact: 044-42115526,

99520 10141(RUBAN)
Visit Our Website:www.peridotsystems.in

Website: www. bigdatahadooptrainingchennai.com

Venue:
KamatchiKrupaApts,
No: 84/8, Ground Floor,
Venkatarathinam main street,
Venkatarathinam Nagar,
LB Road, Adyar, Chennai,
Tamil Nadu – 600020

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